Trends in the surgical treatment for spinal metastasis and the in-hospital patient outcomes in the United States from 2000 to 2009
Surgical treatment for spinal metastasis is still controversial. However, with the improvements in treatment for primary tumors, the survival of patients with spinal metastasis is enhanced. At the same time, surgical technique for spinal metastasis has also improved.
To examine trends in the surgical treatment for spinal metastasis and in-hospital patient outcomes on a national level STUDY DESIGN/SETTING: Epidemiological study using national administrative data, Nationwide Inpatient Sample (NIS) PATIENT SAMPLE: All discharges included in the NIS with a diagnosis code of secondary malignant neoplasm of the spinal cord/brain, meninges, or bone who also underwent spinal surgery from 2000 to 2009 OUTCOME MEASURES: Trends in the surgical treatment for spinal metastasis, in-hospital complications and mortality, and resource use METHODS: The NIS was used to identify patients who underwent surgical treatment for spinal metastasis from 2000 to 2009, using the International Classification of Diseases, 9(th) revision, Clinical Modification (ICD-9-CM) codes. Trends in the surgical treatment for spinal metastasis and in-hospital patient outcomes were analyzed.
From 2000 to 2009, there was an increasing trend in the population growth-adjusted rate of surgical treatment for spinal metastasis (1.15 to 1.77 per 100 000, p < 0.001). Average Elixhauser Comorbidity Score increased over time (2.6 to 3.8, p < 0.001), and overall in-hospital complication rate increased over time (14.8% to 27.7%, p < 0.001), while in-hospital mortality rate and length of hospital stay remained stable over time (5.2% to 4.6%, p = 0.413) (10.6 days to 10.8 days, p = 0.626). Inflation-adjusted mean hospital charges increased more than 2-fold over time ($50390 to $110173, p < 0.001).
During the last decade, surgical treatment for spinal metastasis has increased in the US. The overall in-hospital complication rate and hospital charges increased, whereas the in-hospital mortality rate and length of hospital stay remained stable.
Available from: Rafael De la Garza-Ramos
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ABSTRACT: Study Design. Retrospective study of an administrative database.Objective. To estimate the incidence of sacral fractures in the United States and report short-term outcomes following their surgical management.Summary of Background Data. The incidence of sacral fractures in the U.S. is currently unknown, and these lesions have been associated with significant morbidity following their surgical management.Methods. This study utilized the Nationwide Inpatient Sample (NIS) database for the years 2002 - 2011. All patients with a primary discharge diagnosis of a sacral fracture with and without a neurological injury were identified using ICD-9-CM codes. Patients with a diagnosis of osteoporosis or pathological fracture were excluded. A stepwise multivariate logistic regression analysis was performed to identify factors associated with an in-hospital complication.Results. During the study period, 10,177 patients with a non-osteoporotic sacral fracture were identified, of whom 1,002 patients underwent surgery. Between 2002 and 2011, the estimated incidence of sacral fractures increased from 0.67 per 100,000 persons to 2.09 (P < 0.001). Similarly, the rate of surgical treatment for sacral fractures increased from 0.05 per 100,000 persons in 2002 to 0.24 per 100,000 in 2011 (P < 0.001). Complications occurred in 25.95% of patients and remained steady over time (P = 0.992). Average length of stay significantly decreased from 11.93 days to 9.66 days in the 10-year period (P = 0.023). The independent factors associated with an in-hospital complication were congestive heart failure (OR 3.65; 95% CI, 1.18 - 11.26), coagulopathy (OR 3.58; 95% CI, 1.88 - 6.81) and electrolyte abnormalities (OR 3.28 95% CI, 2.14 - 5.02).Conclusion. During the examined 10-year period, both the incidence of non-osteoporotic sacral fractures and the surgical treatment of these lesions increased in the United States. Between 2002 and 2011, while patient comorbidity increased, in-hospital complication rates remained stable and length of stay significantly decreased over time.
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ABSTRACT: BACKGROUND: Scores derived from comorbidities can help with risk adjustment of quality and safety data. The Charlson and Elixhauser comorbidity measures are well-known risk adjustment models, yet the optimal score for orthopaedic patients remains unclear.
QUESTIONS/PURPOSES: We determined whether there was a difference in the accuracy of the Charlson and Elixhauser comorbidity-based measures in predicting (1) in-hospital mortality after major orthopaedic surgery, (2) in-hospital adverse events, and (3) nonroutine discharge.
METHODS: Among an estimated 14,007,813 patients undergoing orthopaedic surgery identified in the National Hospital Discharge Survey (1990-2007), 0.80% died in the hospital. The association of each Charlson comorbidity measure and Elixhauser comorbidity measure with mortality was assessed in bivariate analysis. Two main multivariable logistic regression models were constructed, with in-hospital mortality as the dependent variable and one of the two comorbidity-based measures (and age, sex, and year of surgery) as independent variables. A base model that included only age, sex, and year of surgery also was evaluated. The discriminative ability of the models was quantified using the area under the receiver operating characteristic curve (AUC). The AUC quantifies the ability of our models to assign a high probability of mortality to patients who die. Values range from 0.50 to 1.0, with 0.50 indicating no ability to discriminate and 1.0 indicating perfect discrimination.
RESULTS: Elixhauser comorbidity adjustment provided a better prediction of in-hospital case mortality (AUC, 0.86; 95% CI, 0.86-0.86) compared with the Charlson model (AUC, 0.83; 95% CI, 0.83-0.84) and to the base model with no comorbidities (AUC, 0.81; 95% CI, 0.81-0.81). In terms of relative improvement in predictive performance, the Elixhauser measure performed 60% better than the Charlson score in predicting mortality. The Elixhauser model discriminated inpatient morbidity better than the Charlson measure, but the discriminative ability of the model was poor and the difference in the absolute improvement in predictive power between the two models (AUC, 0.01) is of dubious clinical importance. Both comorbidity models exhibited the same degree of discrimination for estimating nonroutine discharge (AUC, 0.81; 95% CI, 0.81-0.82 for both models).
CONCLUSIONS: Provider-specific outcomes, particularly inpatient mortality, may be evaluated differently depending on the comorbidity risk adjustment model selected. Future research assessing and comparing the performance of the Charlson and Elixhauser measures in predicting long-term outcomes would be of value.
LEVEL OF EVIDENCE: Level II, prognostic study. See the Instructions for Authors for a complete description of levels of evidence.
Available from: Rafael De la Garza-Ramos
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